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AB0283 IDENTIFICATION OF NEW AUTOANTIBODIES FOR RHEUMATOID ARTHRITIS USING HUMAN PROTEOME MICROARRAYS
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  1. LI Lin1,
  2. Jinhui Tao2,
  3. Hong-Liang Zhang3,
  4. Yu-Jie Tang3,
  5. LI Xin-Ya3,
  6. Qun-Qun Lu1,
  7. Ya-Ling Wang1,
  8. Zi-Wen Zhu1
  1. 1Anhui Medical University Affiliated Provincial Hospital, hefei, China
  2. 2The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, hefei, China
  3. 3Division of Life Sciences and Medicine, University of Science and Technology of China, hefei, China

Abstract

Background Rheumatoid arthritis is an autoimmune disease characterized by symmetrical small arthritis. Anti-cyclic citrullinated peptide antibodies and rheumatoid factor are commonly used to diagnose RA[1]. However, the early diagnosis of RA is sometimes difficult, due to the heterogeneity and negative anti-CCP antibody or RF in some patients. Therefore, it is urgent to find autoantibodies with high sensitivity and specificity as diagnostic markers for RA.

Objectives To screen autoantibodies of RA with high sensitivity and specificity using human proteome microarrays[2].

Methods Firstly, a case-control method was used to analyze the serum antibodies of RA patients using human proteome microarray which composed of 20,000 proteins, and identified RA-related antibodies. Then, expanded the sample size and analyzed the expression of these candidates between RA patients and healthy controls.

Results The serum of five RA patients and five healthy controls were selected to detect the RA-related autoantibodies by microarray, and 25 candidates were screened. Then the IgG and IgM RA-focused microarrays composed of the 25 proteins were screened with additional cohorts of 72 RA patients and 106 healthy controls. The results of IgG protein microarray showed: (1) Expression of these 25 autoantibodies in RA patients was significantly higher than those in healthy controls (P<0.05). (2) There was nodifferentially expressed protein between anti-CCP antibody and RF-negative RA patients (n=18) and anti-CCP antibody and/or RF-positive RA patients (n=54) (P>0.05). (3) ROC analysis showed that the combination of anti-RBPJ, anti-SH3BGR and anti-PAFAH1B3 autoantibody can be highly RA-specific biomarkers, with 66.7% sensitivity and 74.2% specificity, and the area under the curve is 0.734; meanwhile the sensitivity and specificity of the anti-CCP antibody and RF-negative RA patients diagnosis were 77.8% and 65.6%, and the area under the curve was 0.720. The results of IgM protein microarray showed: (1) Only 10 out of the 25 candidates’ expression was significantly higher in RA patients than healthy controls (P<0.05). (2) Compared with anti-CCP antibody and/or RF-positive patients, the expression of anti-PAFAH1B3, anti-RBPJ, anti-SH3BGR, anti-UBA5, anti-ANP32A, anti-PAGE2, anti-SHFM1 and anti-PDE1B was found significantly higher in anti-CCP and RF-negative patients (P<0.05). (3) ROC analysis showed that anti-PAFAH1B3 antibody was identified to diagnose RA with 76.2% sensitivity and 72.9% specificity, and the area under the curve was 0.768; however, there were no significance for the diagnosis of anti-CCP antibody and RF-negative RA patients (P=0.160).

Conclusion The combination of IgG-type antibodies anti-RBPJ, anti-SH3BGR and anti-PAFAH1B3, the IgM-type antibody anti-PAFAH1B3 as well, has high sensitivity and specificity for the diagnosis of RA; especially the IgG-type autoantibody combination has great value for the diagnosis of anti-CCP and RF-negative RA patients.

References [1] Silveira IG, et al. Anti-CCP antibodies have more diagnostic impact than rheumatoid factor (RF) in a population tested for RF. Clinical Rheumatology, 2007. 26(11): p.1883-1889.

[2] Song Q, et al. Novel Autoimmune Hepatitis-Specific Autoantigens Identified Using Protein Microarray Technology. Journal of Proteome Research, 2010. 9(1): p.30-39.

Acknowledgement This work was supported by grants from the National Natural Science Foundation of China (81771774) and the Anhui Provincial Natural Science Foundation (1708085MH191)

Disclosure of Interests None declared

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